An Invitation to an F2F Workshop on the iOBE Software

SEEING BEYOND THE STANDARD OUTCOMES ASSESSMENT

An iOBE Workshop at USM Penang | National Training Week 2025

📅 Friday, 20 June 2025

🕗 8:30 AM – 10:30 AM

📍 Auditorium 3, Kompleks Eureka, USM

👋 A Warm Invitation to Educators and Program Coordinators

If you're an educator or program coordinator who’s looking for a better way to understand and improve your student assessment results, I’d like to personally invite you to join a focused, face-to-face workshop at USM Penang. This session is part of National Training Week (NTW) 2025, and it’s designed to help you rethink how you interpret student outcomes—with the help of a powerful yet easy-to-use software tool called iOBE.

❓ Why This Workshop Matters

Let’s be honest — many of us track student results using averages, total marks, or spreadsheet tables. But often, the outcomes data we collect just sits there — unanalyzed, uncommunicated, and underutilized.

Whether it’s test results, project rubrics, outcome attainments, or course grades, there’s a gap between what the numbers say and what they actually mean. This workshop is here to help bridge that gap, giving you practical ways to see deeper patterns, identify issues, and improve your course outcomes more meaningfully.

💡 What iOBE Brings to the Table

The iOBE software is a smart, lightweight, and versatile tool designed specifically for educators to compute, analyze, and visualize student learning outcomes at both the course and program levels.

At the course level, you can:

• Assess outcomes from tests, assignments, projects, exams, and the overall course
• Generate compact graphs and statistical summaries for quick decision-making
• Communicate results directly to students using visual tools like box plots and population graphs

At the program level, iOBE scales up to:

• Aggregate results from multiple courses
• Support structured CQI and accreditation reportin
• Provide visual clarity when presenting outcomes across course groups

Whether you’re working solo on your course or contributing to program-level reviews, iOBE gives you the insights you need—fast.

🧠 What You'll Experience in the 2-Hour Session

This isn't a theory-only session. It’s designed to be interactive and immediately useful, broken into three engaging parts:

1. Conceptual Session: We’ll start by revisiting the fundamentals of outcome-based assessment, and explore how computed outcomes (rather than raw marks alone) offer deeper insights into student learning and course performance.
2. Software Demonstration: A guided walk-through of how the iOBE software works, using real or sample datasets. You’ll see how outcomes are mapped, processed, and visualized.
3. Practical Hands-On Session: You’ll try it out yourself—entering sample data, generating graphs, and discussing how the outputs can inform your teaching and CQI strategies.

Read more...

Making Assessment Data Meaningful

How Compact Visualizations Support Teaching in Higher Education

As academics in higher education, we’re used to dealing with extensive data from exams, coursework, and projects. Often, though, this valuable data ends up in detailed tables and spreadsheets—thorough but sometimes overwhelming. While we rely heavily on this information, its presentation in numeric form can make it challenging to quickly recognize patterns, interpret performance accurately, or take timely action to improve teaching.

A more effective way to approach assessment results is to visualize the data in compact, meaningful forms. Graphs generated by the iOBE software such as box plots and population plots (see the figure below, plotted against program outcomes) simplify complex information into clear, readable formats, highlighting crucial insights quickly and efficiently.

These visualizations enable educators to quickly identify key patterns and potentially concerning trends in student performance, guiding them in refining and improving their teaching and learning strategies.

Additionally, if the data indicates performance issues arising primarily from student-specific challenges rather than instructional factors, educators can use these insights to provide targeted support, helping students understand their own areas for improvement and encouraging them to proactively engage in enhancing their academic performance.

Why Spreadsheet Tables Can Be Limiting

Most of us have experienced the struggle of sorting through dense spreadsheets. When results are presented only as raw numbers in tables — or reduced to simplistic bar charts that display just a single metric, such as average values — it becomes difficult to grasp the full picture of what’s really happening in our classes. Essential questions may come up but remain tricky to answer clearly:

• How is the overall performance in my course?
• Which learning outcomes are consistently challenging for students?
• Are recent adjustments in teaching methods having any measurable impact?

Answering these questions is considerably easier when the data is presented visually, compact with rich information, allowing quick identification of meaningful trends.

The Power of Visual Summaries

Compact visualizations, like box plots and population distribution graphs, help educators to rapidly understand and interpret data:

• Box plots instantly reveal performance ranges, median values, and variability, highlighting strengths and areas needing attention at a glance.
• Population plots clearly illustrate how each student's achievement compares to the entire class, making it easier to provide targeted support or adjustments.

Such visuals not only enhance individual reflection but also facilitate productive conversations among colleagues and with students themselves.

Effective Across Different Academic Scales

One notable strength of visualizing assessment data is the flexibility it provides across different academic scales:

• Program-level: Visual summaries help coordinators identify long-term trends and achievement patterns, crucial for program reviews, curriculum adjustments, and accreditation.
• Course-group level: A group of lecturers who manage multiple related courses can collectively analyze outcomes, spot common difficulties, and align their teaching practices.
• Single course-level: Individual lecturers gain clearer insights into their semester results, facilitating more precise and timely teaching interventions.
• Micro-level (tests and assignments): Visuals are even useful at the smallest scale, clarifying student responses to particular tests (see the graphs below, plotted against Problem-solving Steps) or assignments, thereby directly informing teaching strategies.

This scalability supports reflective and evidence-based teaching practices, enabling lecturers to continuously refine their approaches.

Driving Better Conversations Through Clearer Data

Ultimately, the greatest value of presenting assessment data visually is its capacity to spark meaningful, practical conversations. With clearer data, educators can quickly pinpoint issues, discuss strategies, and adjust their teaching effectively. Students also benefit from visual clarity—understanding their performance in a broader context empowers them to actively participate in improving their learning.

When we move beyond traditional numeric tables toward concise visual representations, we strengthen the connection between data-driven insights and practical teaching strategies—benefiting educators and learners alike.

Read more...

iOBE Workshop @ UPNM Engineering

We've successfully conducted a full-day workshop titled "Understanding and Using iOBE for the Preparation of Course and Programme Assessment Reports" at UPNM Engineering yesterday (Monday 19/5/2025). Many thanks to Assoc. Prof. Dr Ku Zarina (Academic Deputy Dean) and Assoc. Prof. Dr. Rashdan (HoD for the Aviation Dept.) for the invitation and hosting of this workshop. Huge thanks to all the participants for being good sports throughout the entire full-day sessions.

This is the second iOBE session for the faculty members @ UPNM Engineering, with the practical aim for them to immediately apply iOBE on their course data. The workshop started with the theoretical session to cover the foundations of OBE assessment, the framework of the software, and the interpretation of results from the software.

In the afternoon, we ran the hands-on session where the lecturers trained by running the software on sample courses first, before moving on to run the software on their own courses, as well as aggregating data for several courses together. It was exciting to see that all of them successfully ran the software on their courses (within several seconds of running the software), and being able to see all their students' performance from many different angles that were not seen before.

We hope that this workshop opens up an opportunity for them to see the potentials of seeing into their course and programme data to a deeper level, with the outcomes of having meaningful data to "close the loop" in the CQI process. We wish them all the best for their upcoming preparation of the Course and Programme Assessment Reports.

Read more...

iOBE Software Version 7.0: Major Enhancements and New Features

I'm excited to announce the release of iOBE version 7.0, marking a significant upgrade from iOBE v6.2. This latest version leverages AI analysis, introduces substantial improvements in data visualization, data reporting, computational efficiency, and user experience, while maintaining full compatibility with older input files down to iOBE v6.1. The full version remains freely available to the public, especially for educational institutions seeking robust OBE solutions.

🔹 Key Enhancements in iOBE v7.0

1️⃣ Advanced Visualization and Interactive MATLAB Figures
iOBE now produces high-quality visual outputs as MATLAB figures, giving users enhanced interactivity and flexibility when working with their data. Users can:

✔ Zoom in/out and pan graphs for a closer inspection of data points.
✔ Move and reposition legend boxes for improved clarity.
✔ Resize and refine graph appearances dynamically before exporting them.
✔ Save figures in multiple formats, including PNG, JPEG, PDF, and vector formats (EPS, EMF, SVG), ensuring compatibility with different publishing and reporting needs.

📌 Additional Benefits of using MATLAB Figures

✔ Lossless resizing and scaling, especially useful when exporting figures for research papers, presentations, or reports.
✔ Custom modifications, such as changing axis labels, gridlines, or line styles, even after the figure is generated.
✔ Multi-window support, allowing users to compare multiple datasets simultaneously.

2️⃣ Improved Data Export to Excel
Users can now easily access and analyze iOBE-generated data, which is automatically saved in Excel files. These include:

✔ Student outcomes data at the course, multi-course, and program levels.
✔ Statistical data from box plots (median, quartiles, outliers).
✔ Population distribution data, capturing performance trends at both the course and program levels.

This enhancement allows users to customize their own analysis, integrate data into reports, and use AI tools for deeper insights.

3️⃣ Enhanced User Experience & Front-End Processing
To further streamline workflow and usability, the following upgrades have been implemented:

✔ Improved progress bar tracking: Users now receive detailed updates on the computation stages during software execution, giving them a clearer picture of ongoing processes.

✔ Reduced screen clutter: Data tables are now written directly into Excel files, eliminating unnecessary on-screen outputs and improving processing speed.

✔ Optimized computational processing: The back-end algorithm refinements enhance data processing speed and efficiency, ensuring faster computations and smoother operation.

4️⃣ AI-Assisted Data Analysis Capability
A key enhancement in this version is the ability to leverage AI tools like ChatGPT 4o to perform in-depth analysis of the output files generated by iOBE.

🔹 AI-Driven Insights: The Excel files and visualization charts produced by iOBE contain a substantial amount of computed data. These files can be fed into AI tools like ChatGPT for detailed technical analysis using pattern recognition, statistical analysis, and advanced data analytics.

🔹 Enhanced Decision-Making & CQI: By analyzing iOBE-generated data with AI, educators can gain deeper insights into student performance trends, statistical distributions, and program outcomes. This facilitates better decision-making for Continuous Quality Improvement (CQI) in academic programs.

📌 Important Note: iOBE does not have built-in AI integration. However, its structured output files (Excel + graphs) are compact with detailed information and easily analyzable by AI tools, allowing users to extract more insights beyond what the software presents directly.

5️⃣ User-Friendly Design
While introducing powerful new capabilities, iOBE version 7.0 continues to prioritize ease of use with a streamlined and intuitive interface:

✔ Single-Click Operations – The software features a compact (and the one and only) control panel that users interact with to execute functions with a single click, making data processing effortless. (Shown below is the actual iOBE panel on a full desktop screen, against the background of a self-captured Kinabalu sunrise.)

✔ Simple Input Files – iOBE is designed to work with straightforward input files, ensuring that users can operate the software with minimal setup.

✔ Offline Functionality – iOBE remains an offline tool, providing full data security and privacy, eliminating concerns about exposure to online threats or cloud dependencies, or slow server issues that can impact performance and accessibility.

✔ Comprehensive Documentation – The software is supported by detailed documentation, ensuring that users can easily understand its features, troubleshoot issues, and maximize its capabilities.

📌 Designed for Efficiency: These features make iOBE accessible to all users, from individual educators to institutional decision-makers, without requiring extensive training or technical expertise.

🖥️ Software Availability and Requirements

📌 The Download Links:

1. iOBE Software Version 7.0
2. MATLAB Runtime Compiler R2024b (24.2) for 64-bit Windows
3. Software Manual v7.0
4. Other Documentations

🖥️ System Requirements:

1. Built using MATLAB R2024b (64-bit Windows OS).
2. Requires the MATLAB R2024b compiler (included in the download link above).
3. Can also run on Apple computers but requires a 64-bit Windows OS environment installed first.

🎯 Who Can Benefit from iOBE?
iOBE is designed to support Outcome-Based Education (OBE) assessment at tertiary institutions, but can also be easily adapted for primary and secondary education levels.

✔ Lecturers and teachers can use iOBE for immediate insights into their students’ performance.
✔ Departments and institutions can integrate iOBE into their academic quality assurance processes.
✔ Education researchers can analyze trends in student achievement over time using iOBE’s robust statistical features.

📩 Contact for Training & Support
If your department or institution is interested in implementing iOBE and requires further explanation or training on its effective use for academic programs, please feel free to contact me here.

🔹 Summary of What’s New in iOBE v7.0

✅ New MATLAB interactive figures for refined data visualization & export.
✅ Excel data export for student outcomes, statistics, and performance trends.
✅ Improved front-end processing with detailed progress updates.
✅ More efficient computational algorithms for faster performance.
✅ Full compatibility with older input files (iOBE v6.1+).
✅ AI-assisted analysis compatibility, allowing iOBE data to be analyzed with AI.

Read more...

Online iOBE Seminar @ UPNM Engineering Faculty

An online seminar titled "Implementing iOBE for the Preparation of Self-Assessment Reports (SAR)" was conducted on 12/3/2025 to the group of HoDs at the UPNM Engineering Faculty, for them to evaluate the suitability of the iOBE software in their outcomes assessment and CQI processes.

This session introduced and demonstrated, for the first time, the newly upgraded version of the software - iOBE v7.0 - with enhanced visualization graphics using box plots, new color schemes for easier interpretations on population distribution charts, and extended data computations easily accessible through Excel files.

Many thanks to Assoc. Prof. Dr. Rashdan (Aeronautics HoD) for initiating this session and to Assoc. Prof. Dr. Ku Zarina (Academic Deputy Dean) for organizing and hosting this seminar.

Inshaa Allah, we will follow up soon with a live workshop @UPNM for a more detailed presentation and demonstration of the software.

Read more...